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Data Science Articles & Videos

What Did Ada Lovelace's Program Actually Do?So let’s take a closer look at Lovelace’s program. She designed it to calculate the Bernoulli numbers. To understand what those are, we have to go back a couple millennia to the genesis of one of mathematics’ oldest problems...

Exploring Adversarial ReprogrammingGoogle brain recently published a paper titled Adversarial Reprogramming of Neural Networks which caught my attention. It introduced a new kind of adversarial example for neural networks, those which could actually perform a useful task for the adversary as opposed to just fooling the attacked network. I’m going to walk through the paper in this post, and also add some of my own small modifications to the work they presented in the paper...

Real Talk About Synonyms and SearchWhen I talk to software engineers and product managers about improving their search engines, the conversation often leads to query expansion, and specifically synonyms. A lot of folks who work on search believe that their biggest problem is not having enough synonyms in their dictionary. Synonyms are useful, but they aren’t a cure-all for search problems...

Jobs

Data Scientist - Riot Games - Los AngelesRiot Games was established in 2006 by entrepreneurial gamers who believe that player-focused game development can result in great games. In 2009, Riot released its debut title League of Legends to critical and player acclaim. As the most played PC game in the world, over 100 million play every month. Players form the foundation of our community and it’s for them that we continue to evolve and improve the League of Legends experience.

As Data Scientist, you'll develop advanced machine learning algorithms and statistical models to solve critical problems and help deliver awesome player experiences. You'll partner with product teams to implement data science models into live production systems. You'll bring fresh perspective to inform decision-making toward better player experience by translating player voice into insights using your top-notch modeling and analytic skills...

From GAN to WGANThis post explains the maths behind a generative adversarial network (GAN) model and why it is hard to be trained. Wasserstein GAN is intended to improve GANs’ training by adopting a smooth metric for measuring the distance between two probability distributions...